MCScheduling 1.0
Set of Algorithms for Solving Mixed-Criticality Scheduling
Public Member Functions
MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling Class Reference

The remainder stochastic sampling selection operator implementation. More...

Inheritance diagram for MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling:
MCScheduling.GeneticAlgorithm.CBaseSelectionOperator MCScheduling.GeneticAlgorithm.IConfigurationDependent MCScheduling.GeneticAlgorithm.CGeneticOperator MCScheduling.GeneticAlgorithm.ISelectionOperator

List of all members.

Public Member Functions

 CRemainderStochasticSampling (CConfiguration configuration, bool withReplacement)
 Instantiates a new deterministic sampling selector.
void notify (CConfiguration configuration)
 Invoked when the genetic algorithm is about to be executed.
bool isWithReplacement ()
 Returns true if the selector is with replacement, otherwise, false.
override void select (CPopulation population, CPopulation matingPool, int toSelectCount)
 Selects a chromosome from the specified population according to its fitness.

Detailed Description

The remainder stochastic sampling selection operator implementation.

Author:
Tomas Tunys

Constructor & Destructor Documentation

MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling.CRemainderStochasticSampling ( CConfiguration  configuration,
bool  withReplacement 
)

Instantiates a new deterministic sampling selector.

Parameters:
configurationThe configuration of the genetic algorithm that will utilize this selector.
withReplacementif true, the decimal fractions of the number of expected samples of each chromosome in the mating pool is used in weighted roulette wheel selection, if false, the fractions are treated as probabilities for selection.
Exceptions:
NullReferenceExceptionIf confuguration is null.

Member Function Documentation

bool MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling.isWithReplacement ( )

Returns true if the selector is with replacement, otherwise, false.

Returns:
True if the selection is with replacement.
void MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling.notify ( CConfiguration  configuration)

Invoked when the genetic algorithm is about to be executed.

Parameters:
configurationThe configuration of the genetic algorithm that uses this selector.

Implements MCScheduling.GeneticAlgorithm.IConfigurationDependent.

override void MCScheduling.GeneticAlgorithm.CRemainderStochasticSampling.select ( CPopulation  population,
CPopulation  matingPool,
int  toSelectCount 
) [virtual]

Selects a chromosome from the specified population according to its fitness.

See the description of the algorithm in the description of this class.

Parameters:
populationThe population the chromosome will be selected from.
matingPoolThe mating pool the chromosome will be inserted into.
toSelectCountThe total number of chromosomes to select.

Implements MCScheduling.GeneticAlgorithm.CBaseSelectionOperator.

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